bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/144352

Breastfeeding And Risk Of Asthma, Hay Fever And Eczema

Ek, W.·Karlsson, T.·Azuaje Hernandez, C.·Rask-Andersen, M.·Johansson, A.
View original source ↗Export metadata ↓

Abstract

BackgroundBreastfeeding is commonly proposed to protect against atopic diseases. However, studies aiming to quantify these protective effects have shown conflicting results.\n\nMethodsTo entrench the effects of breastfeeding on risk of asthma, hay fever and eczema, our study included a large study cohort, UK Biobank (N=502,682). Information was collected on whether participants had been breastfeed and on the prevalence of disease. Disease was tested for association with breastfeeding, adjusting or matching for influential covariates.\n\nFindingsA total of 443,068 participants were included in our analyses of which 71{middle dot}2% had been breastfed. The prevalence of asthma was 11{middle dot}4 % and 12{middle dot}7% in the breastfed and non-breastfed groups, and hay fever or eczema (23{middle dot}9% and 24{middle dot}8 % in the two groups respectively. When correcting or matching for potential confounders, we could not see any association between being breastfed and asthma. However, there were increased odds of hay fever and eczema among participants that had been breastfed (P=7{middle dot}78x10-6).\n\nInterpretationThis study reports that breastfeeding is associated with increased odds of hay fever and eczema but it show no evidence for breastfeeding being associated with asthma diagnosis.\n\nFundingThe Swedish Society for Medical Research (SSMF), the Kjell and Marta Beijers Foundation, Goran Gustafssons Foundation, the Swedish Medical Research Council (Project Number 2015-03327), the Marcus Borgstrom Foundation, the [A]ke Wiberg Foundation and the Vleugels Foundation.\n\nEvidence before this studyAtopic diseases affect quality of life for a large part of the human population and pose a very high socio-economic burden. Genetic, environmental, and a number of lifestyle factors influence our risk of developing atopic disorders and high familial prevalence is one of the strongest known risk factors for disease. Several environmental and lifestyle risk factors have already been well established in the scientific community, such as smoking on the risk of developing asthma. Breastfeeding is commonly argued to be protective against atopic diseases. However, studies aiming to quantify these protective effects have shown conflicting results.\n\nAdded value of this studyOur study is, to our knowledge, the largest investigation on how breastfeeding is associated with being diagnosed with asthma, hay fever and eczema at adult age. The study found breastfeeding to be associated with increased odds of being diagnosed with hay fever and eczema during life, while we found no association between breastfeeding and asthma. Our results for hay fever and eczema is in line with the western world hygiene hypothesis, but contradict the general picture of breastfeeding being protective.\n\nImplications of all the available evidenceTo be able to give parents correct advice on lifestyles choices that will protect their kids against atopic diseases, we need to clarify the currently conflicting results on the effect of breastfeeding on risk of atopic diseases. However, these results should not be used to recommend breastfeeding or to discourage it since the present study only investigates the association between breastfeeding history and being diagnosed with asthma, hay fever and eczema during lifetime.\n\nAbbreviations

Source connections

Explore related subjects

epidemiologyPreprint

Keep this discovery

BibTeXRIS

Ek, W., Karlsson, T., Azuaje Hernandez, C., Rask-Andersen, M., Johansson, A.. 2017-05-31. Breastfeeding And Risk Of Asthma, Hay Fever And Eczema. https://doi.org/10.1101/144352

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2018

Translating surveillance data into incidence estimates

Monitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence, i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

epidemiology↗
bioRxiv2018

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology↗
bioRxiv2018

Perfect Counterfactuals for Epidemic Simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a single world approach to matching simulations of controlled epidemics to their exact uncontrolled counterfac-tual. Our method borrows concepts from percolation approaches prune out possible epidemic histories and create potential epidemic graph that can be realized to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models, and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids non-sensical inferences.

epidemiology↗